Course Content

1. Planning of experiments: objectives, selection of treatments, choice of experimental units and response variable.

2. General principles: Randomization, replication, control of error.

3. Completely randomized design, randomization and analysis of variance.Estimation of model parameters.Tests of model assumptions.

4. Design for increased precision:

5. Randomised Complete Block Design: randomisation and data analysis, handling missing data.

6. Latin Square design. Graeco-latin square. Blocking efficiency, management and confounding. Random effects model.

7. Treatment comparisons: orthogonal treatment contrasts, orthogonal polynomials for Quantitative treatments, multiple comparison procedures (use and misuse).

8. Introduction to factorial experiments, interpretation of main effects and interaction. Analysis of covariance.